This article, which can be found here, reviews three cases dealing with multisided markets handled by the Swedish Competition Authority (SCA). The cases concerned online hotel booking, online listings of properties and the market for online orders of take away food. The article tests some predictions on the economic behaviour of platform markets that can be found in the academic literature against the outcomes of these cases.

Platform businesses operate differently from traditional businesses, mainly because they function as matchmakers between different groups of consumers. While economists have developed new models better to explain the particular economic features associated with multisided platforms, the incorporation of these particular economic features into competition law presents certain methodological challenges.

Firstly, while a platform may offer some services that a traditional business does not, one side of the platform’s service offering may directly overlap with that of traditional businesses. Assessing competition between the traditional service and the platform in such circumstances can be challenging. Secondly, multisided platforms pose challenges related to the identification of market power and ‘dominance’.

This points to a related issue, i.e. competition law struggles with identifying the most appropriate metrics for measuring market power in the digital world. Thirdly, the dynamics of competition in digital markets may require certain adjustments to the way competition laws are traditionally enforced in order to reflect certain characteristics of such markets, such as network effects and market tipping. Fourthly, the business models and strategies adopted by digital platforms – e.g. offering free services or platform monetisation strategies – may differ from those adopted in more traditional markets.

The first case concerned most-favoured-nation clauses adopted by Booking.com and Expedia. Both cases focused on the use of best price clauses by online travel agencies (OTAs) in their contracts with affiliated hotels. The OTAs’ business model is based on connecting hotels with consumers, and charging hotels a commission each time a consumer performs a booking through the OTA’s platform. The best price or most favoured nation clauses (MFN clauses) used by Booking and Expedia precluded hotels from offering lower room prices through other sales channels, with some exceptions available for so-called closed user groups.

These clauses were expected to give rise to two effects when applied by various OTAs simultaneously. Firstly, such clauses meant that online platforms did not have to fear that their commissions would lead to higher room prices in their sales channel compared to prices available through other sales channels. Hence, the risk of losing consumers following a commission rate increase was reduced, alongside the risk of customers and hotels freeriding on the OTA’s service. Secondly, any price change applied by a hotel in a channel, perhaps due to a change in commission rates charged by an OTA, must be applied to all sales channels in order to avoid infringing the best price clauses. Both these effects could reduce competition on commission rates between OTAs. Both cases ended with the adoption of commitments aimed at mitigating the aforementioned effects, while simultaneously preserving the viability of the OTA business model by shielding OTAs from free-riding by hotels.

These cases illustrate the complexities associated with investigations into markets where traditional businesses and aggregator platforms coexist and compete. Assessing the extent of demand side substitution (competition) between platforms and businesses is tricky in the presence of simultaneous demand complementarities (additional demand for rooms provided through platforms). Moreover, a competitive assessment of aggregator platforms’ business practices also has to take into account their impact on interbrand competition between traditional businesses.

The second case concerned a merger regarding online real estate platforms that was abandoned when the SCA informed the parties that it was going to try to block it in court.

These real estate platforms act as matchmakers between sellers and prospective buyers of real estate. Sellers are able to advertise their properties, and prospective buyers are able to browse through available properties. Both sides of the market are able to multi-home – i.e. property owners can choose to advertise their properties through one or several of the available platforms, while prospective buyers can choose to view real estate offerings through one or several of the available platforms.

Transactions would occur outside of the advertising platform. As a result, the platforms’ business models were geared toward offering services free of charge to prospective real estate buyers, while charging sellers for advertising their properties upfront. All else being equal, one would expect such a dynamic to reduce sellers’ willingness to multi-home, and thus to reinforce the position of an already existing leader on the market – i.e. the market would be prone to tipping.

Identifying dominance thus became the main issue. A measure of market power would be to identify how much each platform can charge a seller for listing properties on the platform. Assuming one could identify one of the merging platforms as dominant in the market, the question then became how the proposed transaction would affect the constraints, if any, imposed on this dominant company by other platforms on the market. The SCA evaluated these constraints according to a number of metrics, including revenue, number of unique visitors, and number of visitor referrals to real estate agents’ own websites. It emerged that, while significantly smaller, the two merging parties comprised a dominant player and by far the second most important player on the market. Hence, the SCA concluded that the proposed concentration risked eliminating substantial competitive constraints on the dominant merging party.

The last case concerned restrictions imposed by an online food delivery platform.

Onlinepizza was a platform that connected restaurants with pick-up and online delivery customers. This platform adopted exclusivity clauses in its contracts with restaurants, effectively preventing them from multi-homing and affiliating with other platforms.

The most important question here was the extent to which an exclusivity clause toward restaurants can decrease competition between transaction platforms when a large share of restaurants remains unaffiliated. In order for a multi-sided platform like Onlinepizza to grow, it needs to attract both restaurants and (hungry) customers to use its matching service. A platform in its infancy needs to create incentives for adoption as well as identify its most likely early adopters given said incentive structure. In this context, exclusive agreements could pose a threat to competing business models, as they would be effectively excluded from a large part of the consumer base that is relevant to them in the initial phase of introducing a new technology. Whether exclusive contracts are likely to distort competition will, at least in part, depend on the competitive landscape (number and relative sizes of platforms) and whether the market is prone to tipping or not. Establishing market shares and market power in such a dynamic market is almost impossible and, as such, the use of exclusive contracts (once it has been established that contracts do in fact include exclusivity clauses) becomes very difficult to evaluate.

Onlinepizza argued that these clauses merely sought to prevent restaurants from advertising its competitors’ services to Onlinepizza’s customers, and that, in any event, the contracts only covered 5% of restaurants in the relevant market. Despite this, Onlinepizza revised its contractual agreements in order to clarify that restaurant multi-homing is not prohibited as such. Following these contractual amendments, the SCA decided not to pursue the case further.

One might wonder if, under such market conditions, there is any point of intervention by a competition authority. Thus, this case provides an example of how assessments regarding the likelihood of harm in specific markets will influence a competition agency’s prioritisation of certain enforcement activities.

Section IV distils practical insights on how to deal with cases in the digital economy.

A first insight is that online platforms can be both competitors and gatekeepers to traditional businesses, and that when platforms act as gatekeepers their effect on competition is ambiguous. Gatekeepers aggregate the offers of several businesses in order to simplify search and comparison for consumers, leading to increased competition between businesses. They may also have a market demand increasing effect by increasing the matching efficiency between businesses’ products and consumers, leading to higher levels of business. However, inasmuch as it may compete with or restrict the behaviour of traditional businesses, the online platform may simultaneously restrict competition.

A second insight is that, even when several platforms offering similar matching services exist simultaneously in a market, network effects mean that competition between them could be weak. Despite this, smaller platforms may still impose competitive constraints on a dominant platform.

A third insight is that online platforms may require competition agencies to adapt the way they measure market power and define the relevant market. The extreme nature of platform competition, particularly in markets prone to tipping, will require an analysis of several metrics to discern the competitive constraints imposed by different platforms on each other.

A fourth insight is that different types of platforms may require different analytical frameworks. In this regard, the authors argue that affiliation platforms are, all else equal, far more likely to lead to tipping markets when compared to transaction platforms. This is because consumer affiliation tends to be free or at least very cheap on transaction platforms (e.g. OTAs), so customers can easily multi-home and use several platforms. Competition in these markets tends to be for transactions rather than for affiliation, which implies competition takes place in the market rather than for the market. By contrast, affiliation platforms are more likely to lead to single-homing customers, which may make them more prone to tipping.

A final lesson is that the analysis of an agreement’s economic context, taking into account the nature of the goods or services affected and the real conditions of the functioning and structure of the market or markets in question, is necessary in the context of digital platforms to address conduct that would amount to object restrictions in other contexts. This may make enforcement a bit more challenging, since the specificities of the case and the market will have to be thoroughly understood before reaching the conclusion that prima facie object restrictions are indeed restrictions of competition in the particular digital platform market under investigation. Yet, this is a small price to pay for optimal enforcement and for not stifling innovation unnecessarily in fast-moving markets.

Comment:

This is an interesting and useful paper, even if it does not break much new ground: the authors’ insights have been discussed in greater detail in a number of other articles previously reviewed here, as well as in earlier OECD work.

Nonetheless, the article provides an interesting overview of methodological challenges raised by multisided markets, and, in particular, offers examples of how a number of methodological challenges can and have been addressed in practice. What is more, the authors do this without resorting to vague ‘each case is a case, and we must look at the specific facts’ formulations; instead, they go on to derive some guiding principles from these cases that might be deployed in other contexts.